Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

Token serves as the fundamental unit of computation in modern autoregressive models, and generation length directly influences both inference cost and reasoning performance. Despite its importance, existing approaches lack fine-grained length modeling, operating primarily at the coarse-grained sequence level. In this paper, we introduce the Length Value Model (LenVM), a token-level framework that models the remaining generation length at each decoding step. By formulating length modeling as a value estimation problem and assigning a constant negative reward to each generated token, LenVM…